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Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Jundui Mu Pingjuan Zhang Minquan Li Kaifeng Cui Dui Liu Xuhui Zhang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Science And Technology University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

In order to eliminate the calculation error which is generated by the field point selection of finite-difference time-domain method on the interface of medium, this paper introduces a virtual field which is then unfolded by Taylor series, and gives the iterative formula of the nonstandard finite-difference time-domain method (NS-FDTD). The non-standard finite-difference time-domain method (NS-FDTD) is used to simulate plane wave irradiating vertically the novel sub-wavelength metal grating resonator, effects of the thickness of metal layer and the relative dielectric constant to extraordinary transmission characteristic are studied, and the extraordinary transmission mechanism is analyzed using the theory of Fabry-Perot cavity. A novel structure with extraordinary transmission characteristic is designed, and the extraordinary transmission characteristic in 450-900 THz band has also been studied using the method of NS-FDTD, the effect caused by some parameters such as thickness of metal layer, relative dielectric constant of dielectric layer has been given. The results show: as the thickness of the metal layer decreases, the factor of extraordinary transmission increases and moves towards high frequency, what's more, the factor moves towards low frequency as the relative dielectric constant of dielectric layer increases. This study provides a theoretical basis for further research on metal film and its extraordinary transmission mechanism.

关键词： Metals Time-domain analysis Dielectric constant Mathematical model Gratings Cavity resonators

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A Multiband High Gain Grooves Antenna

A Multiband High Gain Grooves Antenna

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Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Ping-Juan Zhang Yawen Song Lichang Huang Minquan Li Anhui Science and Technology University Bengbu China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

In this paper, we present a novel high-gain multiband surface-wave antenna base on extraordinary optical transmission. In order to make the performance of antenna more better we introduced metal wall structure, it can improve the gain of antenna and the half-power beamwidth also have a good embodiment in the E-plane and H-plane. Simulation results show that the gain of proposed antenna can reach more than 12 dB.

关键词： Metals Antenna measurements Gain Surface waves Electromagnetics Transmitting antennas

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Let's play music: Audio-driven performance video generation

arXiv

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arXiv 2020年

作者： Zhu, Hao Li, Yi Zhu, Feixia Zheng, Aihua He, Ran Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China CASIA Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology CAS Beijing China

We propose a new task named Audio-driven Performance Video Generation (APVG), which aims to synthesize the video of a person playing a certain instrument guided by a given music audio clip. It is a challenging task to generate the high-dimensional temporal consistent videos from low-dimensional audio modality. In this paper, we propose a multistaged framework to achieve this new task to generate realistic and synchronized performance video from given music. Firstly, we provide both global appearance and local spatial information by generating the coarse videos and keypoints of body and hands from a given music respectively. Then, we propose to transform the generated keypoints to heatmap via a differentiable space transformer, since the heatmap offers more spatial information but is harder to generate directly from audio. Finally, we propose a Structured Temporal UNet (STU) to extract both intra-frame structured information and inter-frame temporal consistency. They are obtained via graph-based structure module, and CNN-GRU based high-level temporal module respectively for final video generation. Comprehensive experiments validate the effectiveness of our proposed framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Music

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Separable reversible data hiding based on MSB prediction for encrypted 3D mesh models?

arXiv

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arXiv 2019年

作者： Xu, Na Yin, Zhaoxia Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei

Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it to the third party data hider and the cover media can be losslessly recovered after the extraction of the embedded data. Although, in recent years, exten- sive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D mesh models due to its complex data structure and irregular geometry. We propose a separable RDH-ED method for 3D mesh models based on MSB (most significant bit) predic- tion. Firstly, we divide all the vertices of the mesh into the "embedded" set and "reference" set according to topological information between ver- tices, and calculate the MSB prediction errors for the vertices of the "em- bedded" set. Then, bit-stream encryption is used to encrypt the mesh. Finally, data is embedded by replacing the MSB of the encrypted vertex coordinates of the "embedded" set by the additional data bits. Recipient with data hiding key can correctly extract the additional data from the marked encrypted mesh. Recipient with encryption key can recover the mesh perfectly by using MSB prediction. Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the existing RDH-ED method for 3D meshes based on symmetric encryption. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Electromagnetic scattering of two-dimensional rough cylinder based on statistical integral equation

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Journal of Physics: Conference Series 2020年第1期1651卷

作者： Mengnan Zhu Anqi Wang Zhixiang Huang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China.

The study of electromagnetic scattering from Gaussian rough surface is of great significance in radar reconnaissance, target tracking and ocean remote sensing. The moment method (MOM) is a commonly used method with high accuracy. However, in the past research, Monte Carlo method is used to simulate the Gaussian rough surface. In this method, a large number of random simulation operations are carried out, and then a statistical convergence result is obtained by counting the results of all operations. In this paper, the stochastic integral equation method SIEM(Stochastic Integral Equation Method) is proposed to calculate the electromagnetic scattering of Gaussian rough surface. SIEM avoids the difficulty of high difficulty precise modeling and repeated calculation many times, and only single modeling and calculation are carried out for the target problem. In this paper, the electromagnetic scattering of two-dimensional cylinder with Gaussian rough surface is solved, and the effectiveness of SIEM is proved by comparing with mom.

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A Wideband Dual-Band Magneto-Electric Dipole Antenna with Modified Feed Structure 10

A Wideband Dual-Band Magneto-Electric Dipole Antenna with Mo...

引用

10th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2018

作者： Li, Fan Sun, Yufa Zhu, Haoran Fang, Ionzvu Anhui University Ministry of Education Key Lab of Intelligent Computing and Signal Processing Hefei230601 China

ISBN: (纸本)9781538624166

In this paper, a novel wideband dual-band magneto-electric dipole antenna with modified feed structure is proposed. Double-layer patches are utilized to design a pair of folding metal. The double-layer patches dipole can generate two resonant frequencies, which are employed to form a dual-band magneto-electric dipole antenna. A stair-shaped feeding strip with a hexagonal structure is designed to modify the impedance matching. It is found from simulated results that two operation bands with bandwidths of 60% from 1.61 to 2.99 GHz and 31.9% from 4.99 to 6.89 GHz under the return loss level of 10 dB were achieved. The gain of the antenna ranged from 7.56 to 10.56 dBi. Furthermore, low cross-polarization level and low back-radiation are also obtained with the proposed antenna. © 2018 IEEE.

关键词： Natural frequencies

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A wideband dual-polarized magneto-electric dipole antenna for 2G/3G/LTE/WiMAX base stations

A wideband dual-polarized magneto-electric dipole antenna fo...

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2018 IEEE MTT-S International Wireless Symposium, IWS 2018

作者： Lu, Zongzheng Sun, Yufa Zhu, Haoran Zhang, Hongwei Huang, Fei Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

ISBN: (纸本)9781538663462

A wideband dual-polarized magneto-electric (ME) dipole antenna is proposed for 2G/3G/LTE/WiMAX applications. It also applies to 5G (3.3-3.6 GHz). The proposed antenna has Γ-shaped feeding strips to impart a wide impedance bandwidth for it special structure, and a rectangular box-shaped reflector to enhance its stability in radiation patterns and high gain over the operating frequencies. The simulated results show a common impedance bandwidth is 81.2% with standing-wave ratio (SWR) ≤ 1.5 from 1.58 to 3.74 GHz, port-to-port isolation is large than 25dB within the bandwidth. The simulated antenna gains vary from 8 to 10.7 dBi and from 8.2 to 10.6 dBi for port 1 and port 2, respectively. The antenna has nearly symmetrical radiation patterns with low back lobe radiation both in horizontal and vertical planes, and broadside radiation patterns with narrow beam can be also obtained. © 2018 IEEE.

关键词： Base stations

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Graphene based functional devices: A short review

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Frontiers of physics 2019年第1期14卷 23-42页

作者： Rong Wang Xin-Gang Ren Ze Yan Li-Jun Jiang Wei E. I. Sha Guang-Cun Shan Department of Electrical and Electronic Engineering The University of Hong Kong Pokfulam Road Hong Kong China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Instrumentation Science & Opto-electronics Engineering Beihang University Beijing 100191 China Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science & Electronic Engineering Zhejiang University Hangzhou 310027 China California NanoSystem Institute and Department of Chemistry & Biochemistry University of California Los Angeles CA 90095 USA

Graphene is an ideal 2D material system bridging electronic and photonic devices. It also breaks the fundamental speed and size limits by electronics and photonics, respectively. Graphene offers multiple functions of signal transmission, emission, modulation, and detection in a broad band, high speed, compact size, and low loss. Here, we have a brief view of graphene based functional devices at microwave, terahertz, and optical frequencies. Their fundamental physics and computational models were discussed as well.

关键词： graphene terahertz antenna microwave

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Controlled-source electromagnetic signal detection using a hybrid deep learning model: Convolutional and long short-term memory neural networks

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Computers & Geosciences 2025年 204卷

作者： Yecheng Liu Diquan Li Jin Li Yanfang Hu Zijie Liu Xian Zhang School of Geosciences and Info-Physics Central South University Changsha 410083 China Key Laboratory of Metallogenic Prediction of Non-Ferrous Metals and Geological Environment Monitor Ministry of Education Central South University Changsha 410083 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha 410081 China Hunan Provincial Key Laboratory of Finance & Economics Big Data Science and Technology School of Information Technology and Management Hunan University of Finance and Economics Changsha 410205 China

Controlled-source electromagnetic (CSEM) method using a periodic transmitted signal source suppresses random noise by superimposing and averaging the recorded signal over multiple periods. However, it still faces great challenges in strong interference environments. Here we present a CSEM signal detection method based on a hybrid architecture of convolutional neural network (CNN) and long short-term memory neural network (LSTM). Our method improves the quality of the recorded signal by filtering out all the noise periods and retaining the useful signal periods. The core lies in combining the spatial feature extraction capability of CNN with the time series modeling capability of LSTM, which can deeply excavate the feature differences between noise and CSEM useful signal. Meanwhile, a classification model of signal and noise is constructed using a large-scale training dataset. This hybrid model exhibits superior performance compared to other deep learning models such as CNN or LSTM. Also, we propose a novel signal detection mechanism that not only maintains the periodicity of CSEM signal, but also greatly enhances processing efficiency. The results of synthetic and measured data demonstrate that our method can obtain useful signals from CSEM data containing different noise types and significantly improve the quality of sounding curves. In particular, our method is useful for CSEM signal detection in strong interference.

关键词： Controlled-source electromagnetic method Deep learning Noise signal detection

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Detection of Deepfake videos using long distance attention

arXiv

引用

arXiv 2021年

作者： Lu, Wei Liu, Lingyi Luo, Junwei Zhao, Xianfeng Zhou, Yicong Huang, Jiwu School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100195 China School of Cyber Security University of Chinese Academy of Sciences Beijing100195 China Department of Computer and Information Science University of Macau 999078 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

With the rapid progress of deepfake techniques in recent years, facial video forgery can generate highly deceptive video contents and bring severe security threats. And detection of such forgery videos is much more urgent and challenging. Most existing detection methods treat the problem as a vanilla binary classification problem. In this paper, the problem is treated as a special fine-grained classification problem since the differences between fake and real faces are very subtle. It is observed that most existing face forgery methods left some common artifacts in the spatial domain and time domain, including generative defects in the spatial domain and inter-frame inconsistencies in the time domain. And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces in global perspective respectively. The two components are designed using a novel long distance attention mechanism. The one component of the spatial domain is used to capture artifacts in a single frame, and the other component of the time domain is used to capture artifacts in consecutive frames. They generate attention maps in the form of patches. The attention method has a broader vision which contributes to better assembling global information and extracting local statistic information. Finally, the attention maps are used to guide the network to focus on pivotal parts of the face, just like other fine-grained classification methods. The experimental results on different public datasets demonstrate that the proposed method achieves the state-of-the-art performance, and the proposed long distance attention method can effectively capture pivotal parts for face forgery. Copyright © 2021, The Authors. All rights reserved.

关键词： Time domain analysis

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